library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.0 ──
## ✓ ggplot2 3.3.2 ✓ purrr 0.3.4
## ✓ tibble 3.0.4 ✓ dplyr 1.0.2
## ✓ tidyr 1.1.2 ✓ stringr 1.4.0
## ✓ readr 1.4.0 ✓ forcats 0.5.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## x dplyr::filter() masks stats::filter()
## x dplyr::lag() masks stats::lag()
library(plotly)
##
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
##
## last_plot
## The following object is masked from 'package:stats':
##
## filter
## The following object is masked from 'package:graphics':
##
## layout
SNPs <- read_tsv("data/23andMe_complete.txt", comment = '#',
col_types =
cols(
rsid = col_character(),
chromosome = col_factor(),
position = col_integer(),
genotype = col_factor()
))
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = genotype)) +
ggtitle("Total SNPs for each genotype") +
ylab("Total number of SNPs") +
xlab("Genotype")
pdf("images/SNP_example_plot.pdf", width=6, height=3)
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = chromosome, fill = genotype))
dev.off()
## quartz_off_screen
## 2
# Plot graph to a png outputfile
ppi <- 300
png("images/SNP_example_plot.png", width=6*ppi, height=6*ppi, res=ppi)
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = chromosome, fill = genotype))
dev.off()
## quartz_off_screen
## 2
Genotype counts per chromosome
# Version 1 1
p <- ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) +
geom_point()
ggplotly(p)
# Version 2
ggplotly(
ggplot(data = iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species)) +
geom_point()
)
ggplot(data = SNPs, aes(x=chromosome)) +
geom_bar(fill="yellow", color="black") +
ggtitle("Total SNP Count foreach Chromosome") +
xlab("Chromosome") +
ylab("Count")
ggplot(data = SNPs) +
geom_bar(aes(x = chromosome, fill = genotype), color="black") +
ggtitle("Total SNP Count foreach Chromosome") +
xlab("Chromosome") +
ylab("Count") +
theme(legend.position="bottom")
ggplotly(
ggplot(data = SNPs) +
geom_bar(aes(x = chromosome, fill = genotype), color="black") +
labs(title = str_wrap("Total number of SNPs on each chromosome", 25)) +
xlab("Chromosome") +
ylab("Count")
)
ggplot(data = SNPs) +
geom_bar(aes(x = chromosome, fill = genotype), color="black") +
ggtitle("Total SNP Count foreach Chromosome") +
xlab("Chromosome") +
ylab("Count") +
facet_wrap(facets = vars(genotype)) +
theme(legend.position="bottom") +
theme(text = element_text(size=10),
axis.text.x = element_text(size=4))
ggplot(data = SNPs) +
geom_bar(aes(x = chromosome, fill = genotype), color="black") +
ggtitle("Total SNP Count foreach Chromosome") +
xlab("Chromosome") +
ylab("Count") +
facet_wrap(facets = vars(genotype),scales="free_y") +
theme(text = element_text(size=10),
axis.text.x = element_text(size=4)) +
theme(legend.position="bottom")
ggplot(data = SNPs) +
geom_bar(aes(x = chromosome, fill = genotype), color="black") +
ggtitle("Total SNP Count foreach Chromosome") +
xlab("Chromosome") +
ylab("Count") +
theme(legend.position="bottom")
# Plot graph to a png outputfile
ppi <- 300
png("images/SNP.png", width=15*ppi, height=10*ppi, res=ppi)
ggplot(data = SNPs) +
geom_bar(mapping = aes(x = chromosome, fill = genotype)) +
ggtitle("Total SNP Count foreach Chromosome Stacked")
dev.off()
## quartz_off_screen
## 2
Stacked genotype counts per chromosome